Driver Attitudes and Behaviors at Intersections and Potential Effectiveness of Engineering Countermeasures

CHAPTER 4. CONCLUSIONS

This section presents the conclusions from the focus group sessions and from the take-home surveys. As seen above in the Results chapter and appendix D (summary tables of key results), this investigation produced a considerable amount of mostly qualitative data. These results are primarily because of the range of driving scenarios and engineering countermeasures investigated during the focus groups, the number and variability (i.e., gender, age, and location differences) of participants in the study, the open-ended nature of many of the questions, and participants’ willingness to share their opinions openly. In short, there were almost as many unique answers to the questions asked of the focus group participants as there were focus group participants. Such an abundance of data presented the project team with some challenges such as identifying patterns, trends, or specific responses that can justifiably be called out as “conclusions” from the study. Appendix D represents an attempt by the project team to distill and summarize the focus group participants’ responses into some cohesive and interpretable form. The conclusions presented below continue this process, with a decision to focus on highlighting results that reflect the behaviors, attitudes, habits, etc., of all or most of the focus group participants about several key questions.

In keeping with the flow of the actual focus group sessions and with the results presented in chapter 3, the conclusions are organized according to the four intersection scenarios that have been the focus of this investigation: (1) red-light running, (2) left turns at busy intersections, (3) turning left onto a major road with moderate traffic, and (4) rear-end crashes.

For each of the four scenarios, we present our conclusions in the form of answers to three key questions that reflect the technical objectives for the focus groups:

What are drivers most likely to do in this scenario?

Why do drivers engage in these behaviors?

What engineering countermeasures have the most promise for improving traffic safety?

SCENARIO 1: RED-LIGHT RUNNING

Scenario 1 was described to the focus group participants using the graphics in figures 2 and 3 with the following verbal description:: “Approaching a signalized intersection at speed, the light turns yellow. The driver is far enough away from the intersection that he/she can stop if he/she brakes hard, but is likely to enter the intersection on an early red if he/she accelerates.”

What are drivers most likely to do in this scenario?

For this scenario, the focus group sessions indicated that almost all older drivers would stop at the intersection, while many to most middle-aged and younger drivers would go through the intersection. Results from the take-home survey confirmed this general trend. Interestingly, the drivers who indicated that they would go through the light acknowledged that they would do so in a deliberate and purposeful manner based on the current circumstances; i.e., they recognized the risks associated with running a red light under the circumstances described above, yet would often choose to do so anyway.

Why do drivers engage in these behaviors?

For older drivers, stopping is their planned, default driving behavior in this situation. For middle-aged drivers, going through the light is their default strategy, unless they thought that the vehicle in front of them was going to stop. For younger drivers, traffic and driving conditions, being in a rush, and the behaviors of a lead vehicle are all factors that contribute to their going through the light. For most drivers, additional factors that influence their behavior in this scenario include the status of cross traffic, obstructions, roadway conditions (e.g., visibility, traction), congestion levels, and the presence of pedestrians. Younger drivers are generally less likely to go through the light if their parents are in the car with them.

From the take-home surveys, it seems that drivers’ decisions to go through on a late yellow/early red light are primarily based on attitudes/beliefs and the impact of social norms. This encouraging preliminary finding means these factors can be addressed by typical public awareness and similar advertising campaigns. The factors that are more difficult to change, such as habits and experience with critical incidents, had no impact in driver decisionmaking.

What engineering countermeasures have the most promise for improving traffic safety?

Opinions about red-light cameras (countermeasure 1.2) were strongly influenced by both prior experience and age. In the Washington, DC, and Chicago, IL, focus groups (where there are red-light cameras in operation) older drivers did not feel that they improved safety while younger males did feel that they improved safety. In the Seattle, WA, focus groups (where there are no red-light cameras), this trend was reversed. All subjects believed that implementation of red-light cameras should be done fairly with the specific aim of improving safety, not generating revenue.

Opinions about high-visibility traffic lights (countermeasure 1.2) were mixed, with older drivers believing that they would improve safety, and younger drivers (males in particular) believing that they would not help or did not apply to them. Many drivers thought that this countermeasure would work best in suburban or rural areas because it might otherwise get lost in all of the other downtown lights and other traffic control devices.

Opinions about the likelihood of advance traffic light warning signs (countermeasure 1.3) improving safety were very mixed. Most subjects thought that this countermeasure would be most helpful in high-speed areas (i.e., rural and suburban areas).

Opinions about intersection collision warning systems (countermeasure 1.4) were very positive, with many drivers-across all age groups and locations-expressing the opinion that such a countermeasure would definitely aid drivers’ability to stop before entering a potentially dangerous intersection. Some concerns were expressed regarding drivers’ knowledge of the system and if it would provide warning information in time for drivers to safely stop. Many drivers expressed concern that this countermeasure was aimed at the law abiding driver, not the red-light runner. However, most drivers preferred this approach to an in-vehicle only approach.

SCENARIO 2: LEFT TURNS AT BUSY INTERSECTIONS

Scenario 2 was described to the focus group participants using the graphics in figures 4 and 5 with the following verbal description:“Stopped in the middle of an intersection, waiting to make a left turn on a busy street; an oncoming car is also waiting to turn left and makes it difficult to see other vehicles approaching in the next lane. There is no dedicated turning lane and no dedicated turn signal; cars are waiting behind to also turn left (or go straight).”

What are drivers most likely to do in this scenario?

For this scenario, the focus group session data were mixed, with many drivers avoiding this situation altogether (e.g., by taking a different route or making a series of extra right turns). About half of the subjects would wait for the light to change before making the turn and some of the younger drivers indicating that they barge their way into the oncoming lane, thereby forcing other drivers to slow down or stop.

Why do drivers engage in these behaviors?

Many drivers clearly did not trust their ability to judge traffic gaps. When drivers choose to make this maneuver, they are inclined to wait until the safest possible moment, and then accelerate quickly through the intersection. Many drivers expressed concerns about the presence of pedestrians, bicyclists, and low traction conditions, and take these factors into account when making decisions about whether to turn or not. Overall, this maneuver is seen as difficult so many drivers have developed set behavioral strategies that, in their view, reduce the likelihood of a crash.

What engineering countermeasures have the most promise for improving traffic safety?

Opinions about protected left-turn lights (countermeasure 2.1) were very positive, with almost all drivers expressing the opinion that these are very effective at improving safety and expressing the wish that they were available at all busy intersections.

SCENARIO 3: TURNING LEFT ONTO A MAJOR ROAD WITH MODERATE TRAFFIC

Scenario 3 was described to the focus group participants using the graphic in figure 6 with the following verbal description:: “A vehicle is stopped on a minor road with a stop sign, waiting to turn left onto a major road (that has no stop sign); a consistent flow of vehicles going at high speeds is crossing in both directions on the major road.”

What are drivers most likely to do in this scenario?

For this scenario, the focus group sessions indicated that drivers exhibited very mixed behaviors. Slightly more than half of the drivers indicated that they would make the turn as best as they could; slightly less than half of the drivers indicated that they would first turn right, and then find their way back to their original route.

Why do drivers engage in these behaviors?

This scenario is visually demanding, as most drivers alternate their scanning between the left-going and the right-going traffic, while estimating gaps and keeping an eye out for pedestrians and bicyclists.

What engineering countermeasures have the most promise for improving traffic safety?

Opinions about automatic gap detection devices (countermeasure 3.1) were not consistently positive. Interestingly, many Washington, DC, drivers were receptive to this idea and thought that it would be helpful, while almost all drivers from Seattle, WA, and Chicago, IL, did not think that this countermeasure would improve safety. Many drivers might not trust the system and would prefer to make their own gap judgments or rely on other countermeasures. Many drivers were concerned about system accuracy.

Opinions about synchronized adjacent traffic signals (countermeasure 3.2) were generally positive, with well over half of the drivers expressing the opinion that this countermeasure would improve safety.

SCENARIO 4: REAR-END CRASHES

Scenario 4 was described to the focus group participants using the graphic in figures 7 and 8 with the following verbal description: “Approaching an intersection at speed, the car in front stops suddenly when the light changes to yellow; the driver needs to slam on the brakes to avoid a rear-end collision.“

What are drivers most likely to do in this scenario?

For this scenario, drivers select following distances according to some predetermined heuristic-like a 2-second rule-that leaves sufficient space between their vehicle and a lead vehicle. Most drivers try to anticipate a lead vehicle’s actions using cues such as the status of traffic signals, brake lights, or other signs that the vehicle is slowing down. If drivers believe that they will not be able to slow down in time to avoid a crash, many will change lanes or even drive onto a curb or the roadway shoulder.

Why do drivers engage in these behaviors?

More than a third of the focus group participants had been involved in a rear-end near-miss because of a variety of reasons, including tailgating, distraction, making faulty assumptions about other vehicles, or excessive speed.

What engineering countermeasures have the most promise for improving traffic safety?

Opinions about intersection rumble strips (countermeasure 4.1) were decidedly split among the focus group participants, with about half expressing the opinion that they would improve safety and about half believing that they would not improve safety if placed at every intersection. Most drivers thought that they would lose their effectiveness if placed at every intersection because drivers would get used to them; many believed that the noise and vibration would become annoying.

Opinions about the improved skid resistance countermeasure (countermeasure 4.2) were positive, with most focus participants expressing the opinion that they would improve safety and would be preferable to rumble strips. Many believed that a combination of the rumble strips and the improved skid resistance countermeasure would be the most effective intervention.

FUTURE RESEARCH DIRECTIONS

The focus group discussions reported here yielded much useful information on driver behavior and attitudes about intersection driving and to possible safety countermeasures. However, this research has also revealed a number of additional questions that might benefit from future research. The discussion below presents the specific research questions that flow directly from the focus group results. These questions are presented along with the rationale or issues discussed in the focus groups that directly motivated the questions. Also, table 11 provides additional information about the research questions, including candidate methodological approaches for feasibly addressing each one, in addition to general statements about the types of benefits the new research could produce.

Red-Light Running

1.1 Red-Light Camera

Most of the participants were in favor of posting signs indicating where the cameras were located. However, many also mentioned that whether or not they drive cautiously often depends on whether or not they think that there is a camera at a particular intersection.

1. What is the effect of providing warnings about camera locations on red-light running behavior?

2. If cameras are moved around or decoy cameras employed, how does the countermeasure effectiveness vary as a function of the likelihood that a camera is actually located at the intersection?

Some participants mentioned as a drawback the possibility of causing more rear-end crashes as drivers abruptly slow or stop upon seeing the camera. This point has also been used as an argument against red-light cameras elsewhere.(15,16)

3. How do drivers respond when they expectedly and unexpectedly see a camera at an intersection? How does this response change over time (repeated exposure)?

1.2 High-Visibility Traffic Lights

Older drivers seemed to be the only participants that said that this countermeasure would help improve safety. Given that older drivers are less likely to run red lights, this countermeasure may not be as cost-effective as other countermeasures.(4,5) On the other hand, there are several other reasons for addressing older driver safety issues.(17) For example, older drivers are more likely to sustain more serious injuries in crashes than younger drivers, and also that improvements targeted at older driver also benefit the general driving public.

4. What are the aspects of standard traffic signals that make them most difficult to see?

5. How much of an improvement can increased signal visibility make on older driver detection and response to the traffic signals?

1.3 Advance Traffic-Light Warning Signs

Almost all of the drivers mentioned that they felt that this countermeasure would be more effective in areas where traveling speeds were higher.

6. For what speed ranges do drivers find the warning information to be useful (e.g., how does the likelihood that they will use the warning information change with their travel speed)?

Some younger males indicated that they might use the warning information to speed up to make it through the intersection if they were close enough.

7. Can the willingness to use warning information to adopt more aggressive behavior be mitigated by properties of the advanced warning, such as warning timing or placement location?

More generally, several drivers (especially older drivers) indicated that as they approach an intersection, they search for cues indicating that the light may change. Advanced warning signs provide this information in a form that is more accurate and easier to obtain, which reduces cognitive/attention demands on drivers.

8. How much of a reduction in workload, attention, and cognitive demands do advance warning signals provide in comparison to manually identifying whether or not a light is about to change?

1.4 Intersection Collision-Warning System

Many participants indicated that they thought that the system involved too many different types of lights and could be overwhelming or distracting to some users.

9. Can the same effectiveness in getting drivers to stop be achieved with other signal configurations that use fewer lights and components?

Left Turns at Intersections

2.1 Protected Left-Turn Lights

The results of the focus group did not provide suggestions for future research in this area.

Left Turns at Stop-Controlled Intersections

3.1 Automatic Gap Detection

System trust was the primary concern raised by most drivers.

10. Does exposure to the system (e.g., seeing it work accurately) lead to increased trust that the system works, or the opposite conclusion that the warning information is irrelevant?

11. Does driver trust in the system appropriately change to compensate for adverse conditions (e.g., low traction, low visibility, etc.)?

Some drivers were also concerned that drivers might become complacent and rely on the warning information rather than visually checking the actual gaps.

12. Does the presence of a gap detection system affect gap checking behavior (e.g., number of glances at rightward traffic)?

Drivers from Washington, DC (where pedestrian countdown signals are more common) thought that a gap advisory version of the gap detection system would be more effective.

13. What is the relative effectiveness of gap detection and gap advisory systems in terms of driver trust/complacency, ease of understanding the information, and the degree to which drivers compensate for adverse conditions?

3.2 Synchronized Adjacent Traffic Signals

The results of the focus group did not provide suggestions for future research.

Rear-End Crashes

4.1 Intersection Rumble Strips

Most drivers felt that the rumble strips would cause them to refocus their attention on the roadway, but other factors such as habituation would reduce effectiveness.

14. How do both attentive and distracted drivers respond when traversing an intersection rumble strip (e.g., Where do they look? How much do they slow down? etc.)?

15. How does this response change over time with increased exposure and increased likelihood of encountering rumble strips at an intersection?

Many drivers had concerns about car damage and the noise that the rumble strips might cause.

16. Can alternative (more subtle) implementations of the rumble strip be equally effective in drawing attention to the roadway?

4.2 Improved Skid Resistance

Some participants were concerned that other drivers might come to rely on improved skid resistance and inappropriately generalize their improved stopping ability to other untreated locations.

17. Over time, how does experience with improved stopping capabilities at a specific treated intersection affect driver car-following and overall stopping behavior at known treated intersections and other intersections in general?

Table 11. Research questions, candidate research approaches, and benefits from focus group results.

Research Issue

Research Approaches

Benefits of Conducting Research

Red-Light Running

1.1 Red-Light Cameras

1) What is the effect of providing warnings about camera locations on red-light running behavior?

9) Can the same effectiveness in getting drivers to stop be achieved with other signal configurations that use fewer lights and components?

Driving Simulator Studies
Test-Track Studies

Improved countermeasure effectiveness

Left Turns at Intersections

2.1 Protected Left-Turn Lights

None

Left Turns at Stop-Controlled Intersections

3.1 Automatic Gap Detection

10) Does exposure to the system (e.g., seeing it work accurately) lead to increased trust that the system works, or the opposite conclusion that the warning information is irrelevant?

Driving Simulator Studies
Test-Track Studies

Improved countermeasure effectiveness

11) Does driver trust in the system appropriately change to compensate for adverse conditions (e.g., low traction, low visibility, etc)?

Driving Simulator Studies

Further information on countermeasure effectiveness

12) Does the presence of a gap detection system affect gap checking behavior (e.g., number of glances at rightward traffic)?

Driving Simulator Studies
Test-Track Studies

Further information on countermeasure effectiveness

13) What is the relative effectiveness of gap detection and gap advisory systems in terms of driver trust/complacency, ease of understanding the information, and the degree to which drivers compensate for adverse conditions?

Driving Simulator Studies
Test-Track Studies

Further information on countermeasure effectiveness
Improved driver acceptance of countermeasure

3.2 Synchronized Adjacent Traffic Signals

None

Rear-End Crashes

4.1 Intersection Rumble Strips

14) How do both attentive and distracted drivers respond when traversing an intersection rumble strip (e.g., Where do they look? How much do they slow down? etc.)?

Driving Simulator Studies

Further information on countermeasure effectiveness

15) How does this response change over time with increased exposure and increased likelihood of encountering rumble strips at an intersection?

Driving Simulator Studies

Further information on countermeasure effectiveness

16) Can alternative (more subtle) implementations of the rumble strip be equally effective in drawing attention to the roadway?

17) Over time, how does experience with improved stopping capabilities at a specific treated intersection affect driver, car-following, and overall stopping behavior at known treated intersections and other intersections in general?

Driving Simulator Studies

Further information on countermeasure effectiveness

Application of This Methodology to Other Scenarios or Safety Issues

While the previous section discussed how specific issues raised in the focus group may warrant further investigation using other empirical approaches, another avenue for future research is to use focus groups to investigate additional intersection scenarios. More specifically, although the present research addressed scenarios that had the highest crash rates, other scenarios may also warrant attention because of their association with high-severity crash situations, such as crashes involving pedestrians and bicyclists. For example, uncontrolled intersections have the highest rates of pedestrian crashes and high rates of bicyclist crashes.(18) In addition, four-way stop-controlled intersections, and right turns at signalized intersections may also be worth investigating because they often put drivers in direct conflict with pedestrians and bicyclists. Additional focus group research involving these intersection scenarios could provide important insight regarding how drivers anticipate and plan maneuvers (or fail to do so) when pedestrians or bicyclists are present.